code: def __init__(
      self,
      hidden_size: int = 768,
      loss_name: str = "mrc_loss",
      ignore_index: int = -1,
      mrc_label_key: str = "region_class",
      mrc_mask_key: str = "image_region_mask",
      label_dim: int = 1601,
      eps: float = 1e-12,
      use_kl: bool = True,
      *args,
      **kwargs,
  ):
      super().__init__()
      self.loss_name = loss_name
      self.ignore_index = ignore_index
      self.mrc_label_key = mrc_label_key
      self.mrc_mask_key = mrc_mask_key
      self.use_kl = use_kl
  
      # Head modules
      self.region_classifier = nn.Sequential(
          nn.Linear(hidden_size, hidden_size),
          nn.GELU(),
          nn.LayerNorm(hidden_size, eps=eps),
          nn.Linear(hidden_size, label_dim),
      )
  
file_path: mmf/mmf/models/transformers/heads/mrc.py
imports: from typing import Dict
  import torch
  import torch.nn.functional
  from mmf.common.registry import registry
  from mmf.models.transformers.heads.utils import compute_masked_hidden
  from torch import nn, Tensor
label_desc: Use image node_id 1 to create a new MRC object from inherited base classes: nn with example: obj = MRC(hidden_size, loss_name, ignore_index, mrc_label_key, mrc_mask_key, label_dim, eps, use_kl)